System for forecasting slope failure based on sounds from the earth

ABSTRACT

A vibration sensor mounted on a tree on the earth outputs a signal voltage corresponding to a sound from the earth. The signal voltage is continuously measured by a sound observing device and read into a data processing device. The data processing device has a forecasting unit which performs a long-term weather forecasting process based on the value of the signal voltage, i.e., a sound pressure level representing the magnitude of the sound pressure of the sound from the earth. Specifically, the forecasting unit forecasts long-term weather conditions such as warm and cold climates related to high and low temperatures three and six months after the measurement of the sound from the earth, based on changes in the sound pressure level of the measured sound.

This application is a divisional of U.S. patent application Ser. No.10/185,017 filed on Jul. 1, 2002.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a system for and a method of watchingand forecasting long-term weather conditions based on sounds from theearth which are measured by a sensor, and also watching and forecastingchanges in natural phenomena and changes in the weather to watch andforecast slope failures including landslides, debris avalanches, snowavalanches, etc.

2. Description of the Related Art

Heretofore, human and property losses resulting from slope failures suchas landslides or the like which are abnormal natural phenomena havecaused critical damages to regional economies.

If slope failures can be forecast, then it is possible to minimize humanand property losses caused thereby, resulting in large economicadvantages.

Therefore, there have been steady demands for systems to predict slopefailures such as landslides or the like and evacuate local people fromthe hazardous area quickly.

It is desirable to predict long-term weather changes over more than onemonth in order to avoid the danger of natural disasters such as slopefailures, make agricultural activities efficient, and allow variousevents to be scheduled easily.

Heretofore, a correlating process, a periodic process, and an analogousprocess have been employed to predict long-term changes in the weatherover more than one month, i.e., long-term changes in atmosphericconditions and various atmospheric phenomena including snow, rain, wind,thunder, etc.

These predicting processes forecast long-term weather changes accordingto a statistic approach based on empirical rules that are createdbecause physical laws about the weather are not clear enough, unlikeshort-term weather forecasting processes for predicting weather changesover about one week, which are characterized by the use of highlysophisticated meteorological observation devices, a large number ofmeteorological observation sites, and a large number of meteorologicalobservation cycles. The long-term weather forecasting processes predictlong-term weather changes based on an average of predicted data over aplurality of years in the past, e.g., over several decades. Theprediction data produced by these long-term weather forecastingprocesses are not necessarily highly accurate, although these processesare capable of roughly predicting long-term weather changes. It isalmost impossible for the long-term weather forecasting processes topredict accurately whether it will be hot or cold on a particular day inthe future, e.g., after 3 months or 6 months from now.

There are two known techniques to watch a landslide. According to thefirst technique, an Invar wire is extended under tension between twopoints, and the distance between the points is measured from anelongation of the Invar wire. According to the second technique, a waterpressure meter is placed in a hole formed in the ground by boring, and apressure transmitted by a fluid present in a pore in the soil or rock,i.e., a so-called pore water pressure is measured.

The first technique which employs an Invar wire suffers a fatal defectin that it is unable to detect a slope failure which occurs in aposition away from the two points. One solution is to use a number ofInvar wires installed in different positions. However, land areas whichare used for agricultural activities limit the number of locationsavailable for installing Invar wires because Invar wires would lower theefficiency of agricultural activities. The cost of a system formeasuring changes in the distances between points where many Invar wiresare installed is considerably large.

The second technique which employs a water pressure meter placed in ahole formed in the ground is disadvantageous in that it is highlyexpensive and it is impossible to perform boring on all dangerous landregions. Another problem of the second technique is that availableexperimental data are definitely not enough for identifying a directcausal relation between a change in the pore water pressure and a slopefailure. In addition, the second technique cannot meet a quick need forlandslide monitoring because it usually takes several days to form ahole in the ground by boring.

Consequently, there is not any satisfactory process for locally andaccurately predicting a slope failure.

SUMMARY OF THE INVENTION

The applicant of the present application has proposed a new weatherforecasting system for observing sounds from the earth using trees orthe like and predicting highly accurately short-term weather conditionswithin 48 hours or the like based on changes in the observed sounds, asdisclosed in U.S. patent application Ser. No. 09/718,491.

It is an object of the present invention to provide an apparatus for anda method of watching and forecasting long-term weather conditions toproduce long-term and accurate weather forecasts.

Another object of the present invention to provide an apparatus forwatching and forecasting a slope failure such as a landslide or the likewith a simple arrangement, a system thereof, a method of forecasting aslope failure, and a system for watching a slope failure.

According to the present invention, there is provided an apparatus forforecasting long-term weather conditions, comprising means for measuringsounds from the earth, and forecasting means for forecasting long-termweather conditions based on a change in the measured sounds from theearth. With this arrangement, long-term weather conditions in the futurecan be forecast based on changes in the sounds from the earth.

The forecasting means comprises means for forecasting long-term weatherconditions of a day three or six months after the sounds from the earthare measured. It is also possible to forecast weather conditions nine ortwelve months, which are multiples of three months, after the time whenthe sounds from the earth are measured. Specifically, the forecastingmeans forecasts temperatures of a corresponding day of the month threemonths after a day when the sounds from the earth are measured, and theforecasting means forecasts that the temperature on or around thecorresponding day will be lower than a past average temperature of themonth if the sounds from the earth is relatively large, and forecaststhat the temperature on or around the corresponding day will be higherthan the past average temperature of the month if the magnitude of thesounds from the earth is relatively small.

Further, the forecasting means forecasts temperatures of a correspondingday of the month six months after a day when the sounds from the earthare measured, and the forecasting means forecasts that the temperatureon or around the corresponding day will be higher than a past averagetemperature of the month if the sounds from the earth is relativelylarge, and forecasts that the temperature on or around the correspondingday will be lower than the past average temperature of the month if themagnitude of the sounds from the earth is relatively small.

The magnitude of the sounds from the earth comprises an average of themagnitudes of the sounds from the earth such as a moving average of themagnitudes of the sounds from the earth.

Therefore, according to the present invention, it is possible to make along-term weather forecast after three or six months and also obtain anaccurate long-term weather forecast.

According to the present invention, there is also provided a method offorecasting long-term weather conditions, comprising the steps ofmeasuring sounds from the earth, and forecasting long-term weatherconditions based on a change in the measured sounds from the earth. Themethod makes it possible to forecast accurate long-term weatherconditions.

According to the present invention, there is further provided anapparatus for forecasting a slope failure, comprising means formeasuring sounds from the earth, and forecasting means for forecasting aslope failure based on a change in the measured sounds from the earth.The apparatus makes it possible to forecast a slope failure based on achange in the measured sounds from the earth.

The sounds from the earth can be measured through a tree on the earth.Therefore, a slope failure can be forecast with a simple arrangement.The sounds from the earth may be measured through a stake driven in theground rather than a tree on the earth.

The forecasting means may comprise means for forecasting a slope failurewhen the means for measuring sounds from the earth measures a sound fromthe earth having a frequency ranging from 30 to 200 Hz.

The forecasting means may comprise means for presuming a sound producedby a rupture of a root of the tree when the means for measuring soundsfrom the earth measures a sound from the earth having a frequencyranging from 100 to 160 Hz, and presuming a sound produced by a landmovement when the means for measuring sounds from the earth measures asound from the earth having a frequency ranging from 30 to 50 Hz.

The forecasting means may comprise means for presuming a sound producedby an underground water flow when the means for measuring sounds fromthe earth measures a sound from the earth continuously.

The apparatus may further comprise means for, when the means formeasuring sounds from the earth measures the sounds from the earthsimultaneously in at least four sites, calculating a position in whichthe sounds from the earth are produced, based on a simultaneousobservation of the sounds from the earth in the at least four sites.

According to the present invention, there is also provided a system forforecasting a slope failure, comprising means for measuring sounds fromthe earth, means for capturing a ground surface image, and means forforecasting a slope failure based on a change in the measured soundsfrom the earth and a change in the captured ground surface image.

With the above arrangement, it is possible to forecast a slope failurebased on a change in the measured sounds from the earth and a change inthe captured ground surface image. Therefore, a slope failure can bepredicted highly accurately.

The means for measuring sounds from the earth comprises means formeasuring sounds from the earth through a tree on the earth, and themeans for forecasting a slope failure comprises means for capturingimages chronologically and detecting a change in the ground surfaceimage based on a difference between the chronologically captured images.

The means for forecasting a slope failure comprises means forforecasting a slope failure when the means for measuring sounds from theearth measures a sound from the earth having a frequency ranging from 30to 200 Hz and the means for capturing a ground surface image detects achange in the captured ground surface image.

According to the present invention, there is further provided a methodof forecasting a natural phenomenon, comprising the steps of measuringsounds from the earth, and forecasting a change in the naturalphenomenon based on a change in the measured sounds from the earth. Themethod makes it possible to forecast a change in the natural phenomenonbased on a change in the measured sounds from the earth.

According to the present invention, there is further provided a methodof forecasting a slope failure, comprising the steps of measuring soundsfrom the earth, and forecasting a slope failure based on a change in themeasured sounds from the earth.

According to the present invention, there is also provided a method offorecasting a slope failure, comprising the steps of measuring soundsfrom the earth, capturing a ground surface image, and forecasting aslope failure based on a change in the measured sounds from the earthand a change in the captured ground surface image. It is possible withthe method to forecast a slope failure with high accuracy.

According to the present invention, there is also provided a system forwatching a slope failure, comprising means for measuring sounds from theearth, means for capturing a ground surface image, and means forwatching a slope failure based on a change in the measured sounds fromthe earth and a change in the captured ground surface image. The systemmakes it possible to watch a slope failure.

The above and other objects, features, and advantages of the presentinvention will become more apparent from the following description whentaken in conjunction with the accompanying drawings in which preferredembodiments of the present invention are shown by way of illustrativeexample.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a slope failure forecasting apparatusaccording to a first embodiment of the present invention;

FIG. 2 is a cross-sectional view of a vibration sensor of the slopefailure forecasting apparatus shown in FIG. 1;

FIG. 3 is a cross-sectional view taken along line III-III of FIG. 2;

FGI. 4 is a fragmentary perspective view of a tree on which thevibration sensor shown in FIGS. 2 and 3 is mounted;

FIG. 5 is a diagram showing the waveform of a presumed noise sound;

FIG. 6 is a diagram showing a frequency distribution of the presumednoise sound;

FIG. 7 is a diagram showing the waveform of a presumed root rupturesound;

FIG. 8 is a diagram showing a frequency distribution of the presumedroot rupture sound;

FIG. 9 is a diagram showing the waveform of a presumed land movementsound;

FIG. 10 is a diagram showing a frequency distribution of the presumedland movement sound;

FIG. 11 is a diagram showing the waveform of a presumed undergroundwater sound;

FIG. 12 is a diagram showing a frequency distribution of the presumedunderground water sound;

FIG. 13 is a diagram showing the waveform of a wind sound;

FIG. 14 is a diagram showing a frequency distribution of the presumedwind sound;

FIG. 15 is a diagram showing the waveform of a presumed solid objectrolling sound;

FIG. 16 is a diagram showing a frequency distribution of the presumedsolid object rolling sound;

FIG. 17 is a flowchart of a forecasting process carried out by the slopefailure forecasting apparatus shown in FIG. 1;

FIG. 18 is a schematic view of a modification of the slope failureforecasting apparatus shown in FIG. 1;

FIG. 19 is a diagram showing waveforms which are referred to incalculating a sound generating position;

FIG. 20 is a diagram showing three-dimensional coordinate positionswhich are referred to in calculating a sound generating position;

FIG. 21 is a block diagram of a slope failure forecasting systemaccording to a second embodiment of the present invention;

FIG. 22 is a schematic view showing an installed example of the slopefailure forecasting system shown in FIG. 21;

FIG. 23 is a flowchart of a forecasting process carried out by the slopefailure forecasting system shown in FIGS. 21 and 22;

FIG. 24 is a flowchart of a weather forecasting process carried out by along-term weather forecasting process provided by the slope failureforecasting apparatus shown in FIG. 1;

FIG. 25 is a map showing a location where sounds were measured and alocation where temperatures were observed;

FIGS. 26A through 26D are diagrams illustrative of a process offorecasting long-term weather conditions based on sounds from the earth,FIG. 26A showing average measured values of pressure sound levelsobtained from sounds, FIG. 26B showing a curve approximating the averagemeasured values shown in FIG. 26A, FIG. 26C showing a weatherforecasting curve after 3 months, and FIG. 26D showing a weatherforecasting curve after 6 months;

FIG. 27A is a diagram showing a curve of sounds from the earth measuredin August, 2000;

FIG. 27B is a diagram showing a weather forecasting curve for November,2000 which is 3 months after August, 2000;

FIG. 27C is a diagram showing a curve of temperatures measured inNovember, 2000;

FIG. 28A is a diagram showing a curve of sounds from the earth measuredin September, 2000;

FIG. 28B is a diagram showing a weather forecasting curve for December,2000 which is 3 months after September, 2000;

FIG. 28C is a diagram showing a curve of temperatures measured inDecember, 2000;

FIG. 29A is a diagram showing a curve of sounds from the earth measuredin October, 2000;

FIG. 29B is a diagram showing a weather forecasting curve for January,2001 which is 3 months after October, 2000;

FIG. 29C is a diagram showing a curve of temperatures measured inJanuary, 2001;

FIG. 30A is a diagram showing a curve of sounds from the earth measuredin August, 2000:

FIG. 30B is a diagram showing a weather forecasting curve for February,2001 which is 6 months after August, 2000;

FIG. 30C is a diagram showing a curve of temperatures measured inFebruary, 2001;

FIG. 31A is a diagram showing a curve of sounds from the earth measuredin September, 2000;

FIG. 31B is a diagram showing a weather forecasting curve for March,2001 which is 6 months after September, 2000;

FIG. 31C is a diagram showing a curve of temperatures measured in March,2001;

FIG. 32 is a view showing observation spots for observing sounds fromthe earth, placed all over a country; and

FIG. 33 is a view showing an isobaric representation of sounds from theearth all over a country.

DESCRIPTION OF THE PREFERRED EMBODIMENTS 1st Embodiment: Slope FailureForecasting Apparatus

FIG. 1 shows a forecasting apparatus 10 for use as a slope failureforecasting apparatus according to a first embodiment of the presentinvention and also as a long-term weather forecasting apparatusaccording to a third embodiment of the present invention as describedlater on.

The forecasting apparatus 10 serves as an apparatus for forecastingslope failures including landslides, debris avalanches, snow avalanches,etc. As shown in FIG. 1, the forecasting apparatus 10 comprises avibration sensor 12 as a sound measuring means, a sound observing device14, and a data processing device 16.

FIG. 2 shows in cross section the vibration sensor 12, and FIG. 3 showsin cross section the vibration sensor 12 taken along line III-III ofFIG. 2. The vibration sensor 12 is in the form of a moving-coilmicrophone.

As shown in FIGS. 2 and 3, the vibration sensor 12 has a closedcylindrical casing 20 housing therein a magnetizable member body 22 of aconcave cross section which has a recess in which a columnar permanentmagnet 23 and a magnetizable member 24 are fixedly mounted in a layeredstructure. The recess in the magnetizable member 22 is open toward anupper surface 12A of the casing 20.

The magnetizable member 24 and the magnetizable member 22 haverespective upper surfaces lying substantially flush with each other.

A resilient wire is wound around the magnetizable member 24 andfunctions as a coil (moving coil) 26. Damper wires 25 which are of thesame filamentary material as leads 29 at output ends of the moving coil26 are fixed to the side of the casing 20 at angular intervals of 120°.The moving coil 26 is supported on the side of the casing 20 with threewires, i.e., two of the leads 29 and one of the damper wires 25.

The moving coil 26 is movable (vertically in FIG. 2) around themagnetizable member 24, i.e., a cylindrical groove 27 defined betweenthe magnetic bodies 22, 24.

The vibration sensor 12 thus constructed serves to collect solid objectvibration sounds transmitted through a tree τ (see FIG. 4) on the earth.The vibration sensor 12 is held in contact with a solid object whichvibrates as a source of sounds to be collected, i.e., the trunk of thetree τ. When the tree τ vibrates, the casing 20 of the vibration sensor12 is vibrated. When the casing 20 is vibrated, the permanent magnet 23is vibrated, and the magnetic field generated thereby is also vibrated.Since the vibration plate 25 and the moving coil 26 tend to stop due toinertia, the permanent magnet 23 and the moving coil 26 vibraterelatively to each other, changing interlinking magnetic fluxestherebetween. As a result, a signal voltage V is developed by the movingcoil 26.

The vibration sensor 12 thus constructed is able to detect vibrations ina frequency range from 25 Hz to 600 Hz as a sound pressure. Thefrequency range in which the vibration sensor 12 can detect vibrationscan be changed by changing the area of the recesses 25B, the size of themoving coil 26, or the size of the vibration sensor 12 itself.

The signal voltage V developed by the moving coil 26 is supplied vialeads 29 connected to the moving coil 26 to a signal amplifier 40 (seeFIG. 1) in the sound observing device 14.

FIG. 4 shows the vibration sensor 40 mounted on the trunk of the tree τ.The vibration sensor 40 may alternatively be mounted on a branch of thetree τ. Specifically, the vibration sensor 40 is mounted on the tree τby a belt 30 with the upper surface 12A (see FIG. 2) thereof heldclosely against the surface of the trunk of the tree τ. Alternatively,the vibration sensor 40 may be mounted on the tree τ with a side surface12B (see FIG. 2) thereof held closely against the surface of the trunkof the tree τ.

The vibration sensor 40 should preferably be mounted on the tree τ atsuch a height that the sound pressure of sounds P (see FIG. 1) from theearth applied thereto is relatively high when the vibration sensor 40 isvertically vibrated on the trunk of the tree τ.

The sounds P from the earth transmitted to the roots of the tree τ tothe trunk thereof are detected by the vibration sensor 12, which outputsthe signal voltage V depending on the detected sounds P. The signalvoltage V is then transmitted from the vibration sensor 12 to the soundobserving device 14. As described above, sounds observed as the sounds Pfrom the earth include wind sounds and sounds produced when solidobjects such as stones roll on the ground, in addition to sounds fromthe earth.

As sown in FIG. 1, the sound observing device 14 comprises the signalamplifier 40, a noise filter 42, a level meter 44, and a signal outputunit 46. The signal amplifier 40 may comprise a differential amplifierfor reducing the effect of noise on the signal voltage V.

When the signal amplifier 40 is supplied with the signal voltage V fromthe vibration sensor 12, the signal amplifier 40 amplifies the signalvoltage V by 10⁴ times, for example, and outputs the amplified signalvoltage to the noise filter 42.

The noise filter 42 removes noise from the signal voltage V from thesignal amplifier 40, and supplies the signal voltage V to the signaloutput unit 46. Since the sounds P from the earth are present mainly ina frequency band of 1 kHz or lower, the noise filter 42 comprises alow-pass filter (LPF) or a bandpass filter (BPF) (preferably a BPFhaving a pass band ranging from 20 Hz to 650 Hz which covers thefrequency range from 25 Hz to 600 Hz of the vibration sensor 12) forpassing signal components in that frequency band.

The signal voltage V from which noise is removed by the noise filter 42is also supplied to the level meter 44, which indicates the level of thesignal voltage V. Therefore, the user of the forecasting apparatus 10can confirm the magnitude of the sounds P from the earth based on theindication on the level meter 44. The user may determine the height (thevertical position where the sound pressure of the sounds P is relativelyhigh) at which the vibrator sensor 12 is to be mounted on the tree τbased on the magnitude of the sounds P from the earth as recognized fromthe indication on the level meter 44.

The signal output unit 46 outputs the signal voltage V supplied from thenoise filter 42 to the data processing device 16.

The data processing device 16 has a signal input unit 50, a data memory51, a forecasting unit (slope failure forecasting means, long-termweather forecasting means) 52, a clock unit 53, a display unit 54, asound output unit 56, and a printing unit 58. Actually, the dataprocessing device 16 comprises a personal computer constructed of akeyboard, a main body, a display unit, a sound output unit, and anexternal memory such as a hard disk or the like, and the forecastingunit 52 essentially comprises a CPU (Central Processing Unit) (includingperipherals) in the main body. The data memory 51 and the clock unit 53may be incorporated in the forecasting unit 52.

The data processing device 16 includes a ROM (Read Only Memory) forstoring a system program and application programs, a RAM (Random AccessMemory) for use as a working memory, a timer for measuring time, whichis provided by the clock unit 53 having calendar and clock functions,input and output interfaces such as an A/D converter, a D/A converter,etc., a waveform observing board as a waveform observation signalreading and sending unit for displaying the sound pressure of the soundsP from the earth along the vertical axis with time along the horizontalaxis on the display unit 54, and a frequency analyzing board (FFT board)as a frequency analyzing and sending unit for displaying the soundpressure along the vertical axis with frequencies along the horizontalaxis on the display unit 54.

The signal input unit 50 reads the signal voltage V from the signaloutput unit 46 of the sound observing device 14 at suitable timeintervals (e.g., intervals of 1 minute or 10 minutes). The signal inputunit 50 converts the signal voltage V into a digital signal, andsupplies the digital signal as a sound pressure level Vd correspondingto the sound pressure of the sounds P to the forecasting unit 52. Thesignal input unit 50 may alternatively read the signal voltage V basedon a command from the forecasting unit 52.

The forecasting unit 52 performs a process of forecasting a slopefailure based on the sound pressure level Vd from the signal input unit50.

The result of the forecasting process performed by the forecasting unit52 is supplied to the display unit 54, which may comprise a CRT, aliquid crystal display panel, or the like, and also to the printing unit58 such as a printer or the like. The result of the forecasting processis also supplied to the sound output unit 56, which may comprise aspeaker or the like.

FIG. 5 shows the waveform, displayed on the display unit 54, of a soundP1 which is considered to be noise, produced by the waveform observingboard in the data processing device 16 (hereinafter referred to as“presumed noise sound”). In FIG. 5, the horizontal axis represents timeT in the unit [ms] and the vertical axis voltages V in the unit [V]. Thevoltage V is of a relative value.

The waveform of the presumed noise sound P1, etc. can be stored in thememory such as the hard disk or the like in the data processing device16 at processing time intervals based on a program or at desired timesusing the keyboard or the like (not shown).

FIG. 6 shows the frequency spectrum (frequency distribution) of thepresumed noise sound P1 displayed on the display unit 54, produced bythe waveform observing board in the data processing device 16. In FIG.6, the horizontal axis represents frequencies F in the unit [Hz] and thevertical axis voltages V in the unit [V].

FIG. 7 shows the waveform of a sound P2 which is considered to be asound produced upon the rupture of a root of the tree τ (which is notlimited to the tree τ on which the vibration sensor 12 is mounted)(hereinafter referred to as “presumed root rupture sound”).

FIG. 8 shows the frequency spectrum of the presumed root rupture soundP2.

The presumed root rupture sound P2 from the sound output unit 56 has anamplitude of ±2 [V] or less on the waveform, and contains pulsedamplitude peaks occurring at intervals of about 0.2 seconds. Theintervals of the pulsed amplitude peaks are considered to changedepending on the thickness of the root which is ruptured.

The frequency distribution shown in FIG. 8 indicates a large spectrum ina frequency band from 100 to 160 Hz, and the presumed root rupture soundP2 is confirmed in this frequency band. In a frequency band from 30 to60 Hz, a spectrum having values in the range from 0.1 to 0.2 [V] isrecognized even after the presumed noise sound P1 is removed.

The values of the voltage V in the frequency distribution are lower thanthe amplitudes of the voltage V displayed in the waveform because of anerror due to the processing time upon the FFT analysis. The relationshipbetween the waveform and frequency distribution in each of the sounds tobe described below also exhibits the same tendency.

FIG. 9 shows the waveform of a sound P3 which is considered to be asound produced when land moves (hereinafter referred to as “presumedland movement sound”).

FIG. 10 shows the frequency spectrum of the presumed land movement soundP3.

The presumed land movement sound P3 from the sound output unit 56 has anamplitude of ±2 [V] or less on the waveform, and differs from thepresumed root rupture sound P2 in that it is more elongated or has alonger tail than the presumed root rupture sound P2.

The frequency distribution of the presumed land movement sound P3exhibits peaks in a frequency band from 30 to 60 Hz, and leaves aspectrum having values in the range from 0.3 to 0.5 [V] is recognizedeven after the presumed noise sound P1 is removed.

FIG. 11 shows the waveform of a sound P4 which is considered to be asound produced when underground water flows (hereinafter referred to as“presumed underground water sound”).

FIG. 12 shows the frequency spectrum of the presumed underground watersound P4.

The presumed underground water sound P4 from the sound output unit 56 isof a small waveform amplitude value of about ±0.3 [V] or less, butdiffers from the presumed noise sound P1 in that it is repeated severaltimes at intervals of about 0.1 second.

The frequency distribution of the presumed underground water sound P4exhibits a large spectrum in a frequency band from 30 to 60 Hz, but isdifficult to distinguish from the presumed noise sound P1.

FIG. 13 shows the waveform of a sound P5 which is produced when a windblows (hereinafter referred to as “wind sound”). The wind sound P5 isproduced when the leaves of the tree τ rustle or human beings feel awind, and can definitely be recognized as a wind sound rather than apresumed sound.

FIG. 14 shows the frequency spectrum of the wind sound P5.

The wind sound P5 from the signal output unit 56 has a waveformamplitude of ±1 [V] or less, and has substantially similar amplitudesrepeated.

The frequency distribution of the wind sound P5 exhibits a spectrum in awide frequency range from 30 to 180 Hz.

FIG. 15 shows the waveform of a sound P6 which is considered to be asound produced when a mass of soil or a stone rolls on the round when awind is blowing (hereinafter referred to as “presumed solid objectrolling sound”). The presumed solid object rolling sound P6 is difficultto distinguish from the wind sound P5 on the waveform.

FIG. 16 shows the frequency spectrum of the presumed solid objectrolling sound P6.

The presumed solid object rolling sound P6, which is generatedsimultaneously with the wind sound P5, from the sound output unit 56 hasa waveform amplitude of ±1 [V] or less, and has substantially similaramplitudes repeated.

The frequency distribution of the presumed solid object rolling sound P6exhibits peaks in a wide frequency range from 30 to 180 Hz. Though it isdifficult to distinguish the presumed solid object rolling sound P6 andthe wind sound P5 from each other on the waveform and the frequencydistribution because they are observed simultaneously with each other,they can be distinguished from each other with the ear.

A slope failure forecasting process carried out by the forecasting unit52 will be described below with reference to a flowchart shown in FIG.17.

The forecasting unit 52 reads a pressure level Vd from the signal inputunit 50 in step S1.

In step S2, the forecasting unit 52 stores the presumed noise sound P1(waveform and frequency distribution) based on the sound pressure levelVd corresponding to noise in the memory. The presumed noise sound P1 canbe confirmed from the waveform shown in FIG. 5, the frequencydistribution shown in FIG. 6, and the sound from the sound output unit56. In step S2, the waveforms and the frequency distributions of thesounds P2 through P6 are also stored in the memory.

In step S3, the forecasting unit 52 reads the sound pressure level V3 atgiven time intervals.

In step S4, the forecasting unit 52 compares the waveform or frequencydistribution of the sound pressure level Vd read in step S3 with thewaveform or frequency distribution of the presumed noise sound P1, anddetermines whether there is a sound change based on any differencebetween the waveforms or the frequency distributions.

If there is not a sound change greater than a certain level, thencontrol returns to step S3.

If there is a sound change greater than a certain level, then theforecasting unit 52 analyzes the sound P by comparing it with the soundsP2 through P6 stored in the memory in step S5.

If the waveform and frequency distribution of the sound P represent thepresumed root rupture sound P2, the presumed land movement sound P3, orthe presumed underground water sound P4 in step S5, then the sound Pfrom the sound output unit 56 and the stored sound are compared witheach other by the ear. If the sound P is the sound P2, P3, or P4, thenthe forecasting unit 52 forecasts a slop failure in step S6. After stepS6, control returns to step S3 and the forecasting unit 52 repeats theprocessing from step S3.

If the sound P is the wind sound P5 in step S5, then control returns tostep S3 and the forecasting unit 52 repeats the processing from step S3.

If the sound P is the presumed solid object rolling sound P6, then theforecasting unit 52 also forecasts a slop failure in step S6. After stepS6, control returns to step S3 and the forecasting unit 52 repeats theprocessing from step S3.

In step S6, the forecasting unit 52 identifies the type of the sound Pand issues a warning or identifies the type of the sound P and displaysa warning on the screen of the display unit 54.

As described above, the forecasting apparatus 10 according to the firstembodiment measures sounds P from the earth (the wind sound P5, thepresumed solid object rolling sound P6) through the tree τ with thevibration sensor 12 as the sound measuring means, and predicts a slopefailure based on a change in the sounds P from the earth measured by thevibration sensor 12.

Specifically, when the presumed root rupture sound P2 in the frequencyrange from 100 to 160 Hz, the presumed land movement sound P3 in thefrequency range from 30 to 50 Hz, 60 Hz), the presumed underground watersound P4, or the presumed solid object rolling sound P6, other than thepresumed noise sound P1 and the wind sound P5, is observed, theforecasting apparatus 10 forecasts a slope failure.

As a whole, when the forecasting apparatus 10 observes the generation ofa sound P having a frequency range from 30 to 200 Hz while only thepresumed noise sound P1 is being generated at an initial observationstage, the forecasting apparatus 10 can forecast a slope failure.

The forecasting apparatus 10 according to the first embodiment iscapable of forecasting not only a slope failure based on a landmovement, e.g., a landslide, but also a debris avalanche or a snowavalanche, as can be understood by those skilled in the art.

Therefore, the forecasting apparatus 10 according to the firstembodiment can forecast local slope failures highly accurately which hasbeen difficult to forecast.

The forecasting apparatus 10 is simple in arrangement as it isconstructed of the vibration sensor 12, the sound observing device 14,and the data processing device 16.

Since the vibration sensor 12 is mounted on the tree τ by the belt 30,as shown in FIG. 4, the forecasting apparatus 10 can easily beinstalled. The sounds P from the earth can be detected through not onlythe tree τ, but also a solid object such as a stake or the like.

FIG. 18 shows a modified slope failure forecasting apparatus 10Aaccording to the present invention.

As shown in FIG. 18, the slope failure forecasting apparatus 10A hasfour vibration sensors 12, each as a sound measuring means, disposed inrespective at least four positions Q1, Q2, Q3, Q4 on a slope 62extending downwardly from a peak 60, four sound observing devices 14connected respectively to the vibration sensors 12, and a dataprocessing device 16A which reads output signal voltages V from thesound observing devices 14. The data can be transmitted from the soundobserving devices 14 to the data processing device 16A through awireless communication link.

The data processing device 16A successively stores the output signalvoltages V in a memory on a FIFO (First-In First-Out) basis. The memorycan thus store data at present and data over a certain period of time inthe past.

When the data processing device 16A observes sounds P (Pa through Pd)from the earth which have different delay times but have similarwaveforms, e.g., the presumed land movement sound P3 as shown in FIG. 9,substantially simultaneously, the data processing device 16A can specifythe position where the sounds P from the earth are produced, from theknown four positions Q1 through Q4.

Specifically, when the sounds Pa through Pd shown in FIG. 19 areobserved in the respective positions Q1 through Q4 on the screen of thedisplay unit 54 of the data processing device 16A, the sound Pa from theearth which has reached the data processing device 16A at an earliesttime t0, and a linear distance L1 between a position P0 where the soundPa from the earth is produced (a source of the sound P from the earth)and the position Q1 are used as a reference, and distances L2 through L4up to the sounds Pb through Pd which have reached the respectivepositions Q2 through Q4 at respective times t2 through t4 with delaysare determined according to “delay time×speed at which sounds arepropagated in the ground”. The speed at which sounds are propagated inthe ground is measured in advance.

If the time required for sound waves to travel from the position P0 tothe position Q1 is represented by t and the speed at which sounds arepropagated in the ground by S, then the distances L1 through L4 can bedetermined by the following equations:L 1=t×S   (1)L 2=(t+t 2−t 1)×S   (2)L 2=(t+t 3−t 1)×S   (3)L 2=(t+t 4−t 1)×S   (4)

If the position of the sounds P from the earth (see also FIG. 19) in athree-dimensional coordinate system is indicated by P0(x,y,z) as shownin FIG. 20, then the following equations (5) through (8) are satisfied:L 1=((x−x 1)²+(y−y 1)²+(z−z 1)²)^(1/2)   (5)L 2=((x−x 2)²+(y−y 2)²+(z−z 2)²)^(1/2)   (6)L 3=((x−x 3)²+(y−y 3)²+(z−z 3)²)^(1/2)   (7)L 4=((x−x 4)²+(y−y 4)²+(z−z 4)²)^(1/2)   (8)

By putting the right sides of the equations (5) through (8) in the leftsides of the equations (1) through (4), the position of the sounds Pfrom the earth can be determined from the resultant equations becausethe unknowns are the time t required for sound waves to travel from theposition P0 to the position Q1 and the position of the sounds P from theearth. As can be seen from FIG. 20, the equations (5) through (8) areequations for determining the lengths of the edges of a triangularpyramid having a vertex P0 and bases Q2, Q3, Q4.

2nd Embodiment: Slope Failure Forecasting System

FIG. 21 shows a slope failure forecasting system 100 according to asecond embodiment of the present invention. The slope failureforecasting system 100 has a function to forecast a slope failure and afunction to watch a slope failure, and hence includes a function as aslope failure watching system.

Those parts of the slope failure forecasting system 100 shown in FIGS.21 and 22 which are identical to those of the forecasting apparatusshown in FIGS. 1 and 18 are denoted by identical reference characters,and will not be described in detail below.

The slope failure forecasting system 100 basically comprises a pluralityof vibration sensors 12 as a means for measuring sounds P from theearth, and a digital video camera 102 as a ground surface imagecapturing means for capturing an image of a slope 62 as a groundsurface. The slope failure forecasting system 100 may have a singlevibration sensor 12 if the position P0 of sounds P from the earth doesnot need to be identified.

The slope failure forecasting system 100 also has a data processingdevice 116 having a forecasting unit 152 which functions as a means forwatching a slope failure or a means for forecasting a slope failurebased on an output from a forecasting unit 52A which is included in adata processing device 16B to forecast a slope failure from a change insounds P from the earth, and also based on a change in the image of theground surface which is captured by the digital video camera 102.

The data processing device 116 comprises a personal computer, and has,in addition to the forecasting unit 152, a camera controller 108 forcontrolling the digital video camera 102, a printing unit 158 comprisinga printer or the like, a display unit 154 comprising a plurality ofdisplay devices such as CRTs or the like, a sound output unit 156 suchas a speaker or the like, a communication processor 180 forcommunication with an external device, and a display processor 118 forcontrolling the printing unit 158, the display unit 154, and the soundoutput unit 156.

The display processor 118 and the communication processor 180 arecontrolled by the forecasting unit 152. The camera controller 108, theforecasting units 52A, 152, the display processor 118, and thecommunication processor 180 are interconnected by a bus 120.

The digital video camera 102 has a field of view containing the slope 62and also targets TA disposed in suitable positions on a tree τ (a tree τin FIG. 22) and the slope 62 and used as subjects for positioning thedigital video camera 102.

The digital video camera 102 is disposed in a position 122 which isspaced from the slope 62 and assumed to be immovable.

Operation of the slope failure forecasting system 100 thus constructedwill be described below with reference to a flowchart shown in FIG. 23.

Steps S11 through S15 shown in FIG. 23 correspond to steps S1 through S5shown in FIG. 17 of the sound observing device 14 in the forecastingapparatus 10 and will not be described in detail below.

After step S15 in which a sound P from the earth other than the presumednoise sound P1 is confirmed, the camera controller 108 controls thedigital video camera 102 to start capturing an image of the slopeincluding the targets TA at every given interval of time in step S16.Actually, before a sound P from the earth other than the presumed noisesound P1 is confirmed in step S15, the digital video camera 102 capturesseveral images a day, and if a sound P from the earth other than thepresumed noise sound P1 is confirmed in step S15, then the digital videocamera 102 captures an image more frequently, i.e., at every giveninterval of time, e.g., every 5 minutes, every 10 minutes, every 30minutes, every hour, depending on the type and amplitude of the sound.It is preferable to capture image data with the digital video camera 102and read sound data with the sound observing device 14 synchronously atthe same time.

In step S17, a process of watching and forecasting a slope failure iscarried out based on the confirmed sound and the captured images.

Specifically, the forecasting unit 152 determines the difference betweenpixels of chronologically adjacent two of the images that have been readsuccessively on a time-series basis by the digital video camera 102, forthereby detecting a change in the ground surface image.

If the forecasting unit 152 detects a change in the ground surface imagewhich is of at least a certain value represented by the differencebetween pixels that is not considered to be of a noise level, then sincethe change in the sounds P from the earth has been confirmed in stepSIS, the forecasting unit 152 forecasts that there is a higherpossibility of a slope failure.

In step S17, the forecasting unit 152 calculates the position P0(x,y,z)of the sound P from the earth according to the above equations (1)through (4). A chronological change in the position P0(x,y,z) of thesound P from the earth can also be used to forecast a slope failure.

In step S18, an image of the slope 62 in which an area showing a largechange in the ground surface image is identified, e.g., marked, isdisplayed on the display unit 154, and the type of the sound confirmedin step S15, whether it is the presumed root rupture sound P2 or thepresumed land movement sound P3, is displayed. The waveform andfrequency distribution of the sound P from the earth can also bedisplayed simultaneously. In addition, the sound output unit 156 mayoutput the sound P from the earth and a warning. It is also possible todisplay, on the display unit 154, a three-dimensional representation ofthe position P0 of the sound P from the earth (including its change).

The printing unit 158 outputs a hard copy showing the image displayed onthe display unit 154, the waveform and frequency of the sound P from theearth, or the change in the position P0 of the sound P from the earth.

The sound data of the sound P from the earth and the image data of theground surface, which have been acquired by the slope failureforecasting system 100, are transmitted to an external data collectingapparatus through a wired or wireless circuit network in step S19.

As described above, the slope failure forecasting system 100 shown inFIGS. 21 and 22 watches a slope failure based on a change in the sound Pfrom the earth and a change in the ground surface image, and forecasts aslope failure based on the result of the watching. Consequently, theslope failure forecasting system 100 is capable of forecasting a slopefailure highly accurately.

3rd Embodiment: Long-Term Weather Forecasting Apparatus

As described above, the forecasting apparatus 10 shown in FIG. 1 doublesa long-term weather forecasting apparatus according to a thirdembodiment of the present invention.

The forecasting apparatus 10 which serves as a long-term weatherforecasting apparatus comprises a vibration sensor 12 as a means formeasuring sounds propagated through the ground, a sound observing device14, and a data processing device 16.

When the forecasting apparatus 10 functions as a long-term weatherforecasting apparatus, the vibration sensor 12 and the sound observingdevice 14 function in the same manner as those of the forecastingapparatus 10 which functions as a slope failure forecasting apparatus,but the data processing device 16 performs a modified process.

The signal input unit 50 of the data processing device 16 reads thesignal voltage V from the signal output unit 46 of the sound observingdevice 14 at every interval of time. For example, the signal input unit50 reads the signal voltage V continuously for 30 seconds at every 10minutes. The signal input unit 50 converts the signal voltage V into adigital signal as a sound pressure level Vd corresponding to the soundpressure of the sounds P. The sound pressure level Vd is supplied to andstored in the data memory 51 by the forecasting unit 52. At this time,the data memory 51 stores successive sound pressure levels Vd astime-series data, each at an address represented by year, month, date,time (Yyyy; Mm; Dd; Hh; Mm).

The data memory 51 thus stores data of the sound pressure levels Vd forone day, five days, or one month, which have been read continuously for30 seconds at every 10 minutes.

The forecasting unit 52 performs a long-term weather forecasting processbased on the data of the sound pressure levels Vd stored in the datamemory 51. Specifically, the forecasting unit 52 determines an averageof the data of the sound pressure levels Vd for one day, or determines amoving average of data of the sound pressure levels Vd for several days,arranges the average values for one month on a time-series basis, andproduces a long-term weather forecast based on the average values thusarranged. If one month of data has not been accumulated in the datamemory 51, then the forecasting unit 52 sends a command to record thesignal voltage V continuously to the signal input unit 50.

The weather forecast obtained by the forecasting unit 52 is stored inthe data memory 51, and then supplied to the display unit 54 such as aCRT, a liquid crystal display panel, or the like, and also to theprinting unit 58 such as a printer or the like.

The data of the sound pressure levels Vd are converted into a soundsignal, if necessary, by the forecasting unit 52. The sound signal isoutputted as a sound by the sound output unit 56 such as a speaker orthe like.

A weather forecasting process which is carried out by the forecastingapparatus 10 thus constructed will be described below with reference toFIG. 24. The signal processing in the weather forecasting process ismainly carried out by the forecasting unit 52.

A sound A transmitted through the tree τ to the vibration sensor 12 isconverted into a signal voltage V by the vibration sensor 12. The signalvoltage V is continuously supplied to the signal input unit 50 of thedata processing device 16 through the sound observing device 14 whichincludes the signal amplifier 40, the noise filter 42, and the signaloutput unit 46.

The signal voltage V that is continuously supplied to the signal inputunit 50 has a frequency band from 16 Hz to 1600 Hz. The signal voltage Vhas large amplitudes in a frequency range from 30 Hz to 700 Hz and afrequency range from 30 Hz to 200 Hz in the above frequency band.

While the signal voltage V corresponding to the sound A is beingcontinuously supplied to the signal input unit 50, the clock unit 53having calendar and clock functions sends a trigger signal to theforecasting unit 52 in every 10 minutes in step S1.

In step S2, the forecasting unit 52 instructs the signal input unit 50to read data of sounds from the earth for 30 seconds from the time ithas received the trigger signal. The signal input unit 50 then convertsthe signal voltage V into digital data continuously for 30 seconds, andtransmits the digital data as a sound pressure level Vd to theforecasting unit 52. The digital data of the sound pressure level Vd for30 seconds is then stored in the data memory 51.

In step S3, the signal input unit 50 processes the digital data of thesound pressure level Vd for 30 seconds which is stored in the datamemory 51, and determines a sound pressure level Vd as a representativevalue of the digital data for 30 seconds.

Specifically, the signal input unit 50 converts the digital data of thesound pressure level Vd for 30 seconds according to a fast Fouriertransformation, and determines a value of greatest power in the obtainedfrequency spectrum as a sound pressure level Vd as a representativevalue of the digital data for 30 seconds.

In step S4, the data of the sound pressure level Vd thus determined asthe representative value of the digital data for 30 seconds isdetermined as the data of the sound pressure level Vd at the timemeasured in step S1 (when the trigger signal was produced). Thedetermined data is stored in the data memory 51 at an addressrepresented by the year, month, date, time when it was measured.

In step S5, the forecasting unit 52 determines whether the data of thesound pressure levels Vd stored at respective addresses in the datamemory 51 have been accumulated for one day, i.e., the day when the dataare measured, or not. If the answer to step S5 is negative, and the dataof the sound pressure levels Vd determined every 10 minutes have notbeen accumulated for one day in the data memory 51, then the forecastingunit 52 repeats the processing in steps S1 through S5 to accumulate dataof sound pressure levels Vd determined every 10 minutes in the datamemory 51.

If the answer to step S5 is affirmative, and the data of the soundpressure levels Vd determined every 10 minutes have been accumulated forone day in the data memory 51, then control goes to step S6.

In step S6, the forecasting unit 52 averages the data of the soundpressure levels Vd determined for one day, e.g., determines anarithmetic mean of the data.

In step S7, the forecasting unit 52 stores the average data as data of asound pressure level Vd as a representative value of the day in the datamemory 51 at an address represented by the year, month, date, time.

In step S8, the forecasting unit 52 determines whether the data of soundpressure levels Vd as representative values of the days have beenaccumulated for one month or not. Until the answer to step S8 becomesaffirmative, the processing in steps S1 through S8 is repeated.

If the data of sound pressure levels Vd as representative values of thedays have been accumulated for one month, then the answer to step S8becomes affirmative.

In step S9, the forecasting unit 52 produces a long-term weatherforecast based on the data, accumulated for one month, of sound pressurelevels Vd as representative average values of the days.

FIG. 25 shows the location where a long-term weather forecasting processcarried out by the forecasting apparatus 10 shown in FIG. 1, and thespot where temperatures were observed for the purpose of comparison withthe results of the long-term weather forecasting process thus carriedout.

Sounds from the earth were measured and the long-term weatherforecasting process was carried out using a tree τ in a lot in NagaokaCity, Niigata Prefecture, Japan owned by the assignee of the presentapplication. The tree τ on which the vibration sensor 12 was mounted formeasuring sounds from the earth was a Japanese fir, about 2.5 m high andabout 5 cm diameter. The vibration sensor 12 was mounted on the tree τat a height of about 1 m for measuring sounds P from the earth. A signalvoltage V produced by the vibration sensor 12 from sounds P from theearth was read into the sound observing device 14. The data processingdevice 16 produced a long-term weather forecast, i.e., forecasttemperature differences in a long range at the measured spot.

Temperatures were measured in a snow removal base located inNakanoshima-cho, Niigata Prefecture, which is 5.9 km spaced straightfrom the spot where the sounds from the earth were measured.

Since the spots where the sounds from the earth and the temperatureswere measured are positioned in a plain, almost no geographical factorsare considered to affect the long-term weather forecast.

FIGS. 26A through 26D show a concept of the long-term weatherforecasting process thus carried out.

FIG. 26A shows a chronological array (see •) of sound pressure levels Vdof days over one month (month X) which were processed by the dataprocessing device 16. Each of the sound pressure levels Vd is an averagevalue of the data of sound pressure levels Vd in one day stored in thedata memory 51. In FIG. 26A, the sound pressure level Vd represented bythe vertical axis increases, i.e., the amplitude of the sound pressurelevel Vd increases, downwardly along the vertical axis.

FIG. 26B shows a curve Ca approximating changes in the sound pressurelevel Vd represented by moving averages of sound pressure levels Vdcalculated for the respective days. The curve Ca is also referred to asa measured curve Ca or a measured waveform Ca. For a betterunderstanding of the present invention, a curve will also be consideredto be a waveform.

The moving average referred to herein is an average of data measuredover several day. For example, if the moving average is an average ofdata measured over 3 days, then the moving average of the measured datafor a certain measured day is indicated by ((Vd of the measured daypreceding the certain measured day)+(Vd of the certain measured day)+(Vdof the measured day following the certain measured day))/3. The graphshown in FIG. 26B represents a curve approximating changes in the soundpressure level Vd, which is produced by applying polynomialapproximation to the moving average data of FIG. 26A. The moving averagewas employed for the purpose of smoothing abrupt changes in the sounds Pfrom the earth. The moving average may be obtained over a number of daysranging from 2 days to several days, rather than 3 days. The long-termweather forecasting process may be carried out without using the movingaverage, or using another averaging process.

FIG. 26C shows a long-term weather forecasting curve Cb of the month(X+3) after 3 months from the measured month X. In FIG. 26C, themeasured curve Ca which approximates the sound pressure levels Vd shownin FIG. 26B is used as a long-term weather forecasting curve Cb of themonth (X+3). As the amplitude of the sound pressure level Vd of themeasured month X is large, it is determined that the climate will becold with lower temperatures in the month (X+3) than a monthly averagetemperature in the past. If the amplitude of the sound pressure level Vdof the measured month X is small, it is determined that the climate willbe warm with higher temperatures in the month (X+3) than a monthlyaverage temperature in the past. The long-term weather forecasting curveCb (FIG. 26C) of the month (X+3) represents a waveform which is in phasewith the measured curve Ca (FIG. 26B) of the month (X+3). In the graphshown in FIG. 26C, the horizontal axis plotted centrally between hotterand colder levels represents the monthly average temperature in thepast. The monthly average temperature in the past represents an averagevalue of temperatures of the same month in several years in the past.

More specifically, in FIGS. 26B and 26C, a temperature forecast is madedepending on the magnitude of the sound pressure level Vd of the soundsP from the earth measured on a certain day of the month X (e.g., the 2ndday of the month X). For example, a temperature forecast is made toindicate that it will be colder than the monthly average temperature inthe past, three months after the day when relatively large sounds weremeasured, e.g., on the corresponding day (the 2nd day) of the month(X+3), and it will be warmer than the monthly average temperature in thepast, three months after the day when relatively small sounds weremeasured, e.g., around the corresponding day, i.e., the 4th day of themonth (X+3).

FIG. 26D shows a long-term weather forecasting curve Cc of the month(X+6) after 6 months from the measured month X in FIG. 26B. In FIG. 26D,the average value of the measured curve Ca of the month X is defined asa reference level, and the waveform of the measured curve Ca is invertedabout the reference level, thus producing the long-term weatherforecasting curve Cc. Therefore, the reference level represents amonthly average temperature of the month (X+6).

According to the weather forecast of the month (X+6) shown in FIG. 26D,unlike the weather forecast of the month (X+3) shown in FIG. 26C, as theamplitude of the sound pressure level Vd of the month X is large, it isdetermined that the climate will be warmer with relatively hightemperatures in the month (X+6), and if the amplitude of the soundpressure level Vd of the month X is small, it is determined that theclimate will be colder with relatively low temperatures in the month(X+6). Stated otherwise, the long-term weather forecasting curve Cb(FIG. 26D) of the month (X+6) represents a waveform which is in oppositephase with the measured curve Ca (FIG. 26B) of the month X.

More specifically, in FIGS. 26B and 26D, a temperature forecast is madedepending on the magnitude of the sound pressure level Vd of the soundsP from the earth measured on a certain day of the month X (e.g., the 2ndday of the month X). For example, a temperature forecast is made toindicate that it will be warmer with relatively high temperatures, sixmonths after the day when relatively large sounds were measured, e.g.,on the corresponding day (the 2nd day) of the month (X+6), and it willbe colder with relatively low temperatures, six months after the daywhen relatively small sounds P from the earth were measured, e.g.,around the corresponding day, i.e., the 4th day of the month (X+6).

If the difference between the temperatures at the start and end of amonth is large, e.g., if there is a 5° C. temperature difference of 5°C. or greater between the start and end of a month, then the referencelevel referred to above should preferably be a straight lineinterconnecting the value of the approximate curve at the start of themonth (corresponding to the temperature at the start of the month) andthe value of the approximate curve at the end of the month(corresponding to the temperature at the end of the month), rather thanthe average of the approximate curve (corresponding to the monthlyaverage temperature). If the data of sound pressure levels Vd have beenaccumulated over many years, then the data of sound pressure levels Vdof the corresponding months may be averaged to calculate an arithmeticmean, which may be used as the reference level.

Specific examples of the long-term weather forecasting process describedabove with reference to FIGS. 26A through 26D will be described below.

FIG. 27A shows a measured curve 100 based on changes in the soundpressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 25), inAugust, 2000. FIG. 27B shows a weather forecasting curve 102 of along-term weather forecast in the vicinity of Nagaoka City in November,2000 (after three months), predicted from the results of the soundpressure levels Vd. FIG. 27C shows a curve 104 of actual temperaturechanges in the snow removal base (see FIG. 25) in the same month(November, 2000).

As shown in FIG. 27A, the sound pressure level Vd in August has itswaveform amplitude smaller in some days at the start of the month, buttending to become larger as a whole toward the end of the month. It canthus be predicted that it will be cold up to the end of November, fromthe weather forecasting curve 102 of the long-term weather forecast forNovember shown in FIG. 27B based on the measured data in August. Thecurve 104 of actual temperature changes (also referred to as“temperature waveform”) shown in FIG. 27C indicates that the temperaturewas about 10° C. at the start of the month, but dropped nearly to 0° C.at the end of the month. First snowfall was recorded in the NiigataPrefecture on November 28. The forecasting apparatus 10 according to thepresent invention is thus capable of forecasting warm and cold climateshighly accurately, and also forecasting first snowfall highlyaccurately.

FIG. 28A shows a measured curve 106 based on changes in the soundpressure level Vd in Nagaoka City, Niigata Prefecture (FIG. 25), inSeptember, 2000. FIG. 28B shows a weather forecasting curve 108 of along-term weather forecast in the vicinity of Nagaoka City in December,2000 (after three months), predicted from the results of the soundpressure levels Vd. FIG. 28C shows a curve 110 of actual temperaturechanges in the snow removal base (see FIG. 25) in the same month(December, 2000).

As shown in FIG. 28B, the weather forecasting curve 108 of the long-termweather forecast indicates a cold climate with lower temperatures thanthe monthly average temperature in the past throughout December. It canthus be predicted that it will be cold up to the end of December, basedon the measured data in September. The curve 110 of actual temperaturechanges shown in FIG. 28C indicates that the temperature of about 0° C.continued from the start of the month, and dropped below 0° C. at theend of the month. Lingering snow, i.e., snow that remains unthawed untilthe snow-thawing season, was recorded in plains in the NiigataPrefecture on December 26. The forecasting apparatus 10 according to thepresent invention is thus capable of forecasting warm and cold climateshighly accurately, and also forecasting lingering snow highlyaccurately.

FIG. 29A shows a measured curve 112 based on changes in the soundpressure level Vd in Nagaoka City, Niigata Prefecture (FIG. 25), inOctober, 2000. FIG. 29B shows a weather forecasting curve 114 of along-term weather forecast in the vicinity of Nagaoka City in January,2001 (after three months), predicted from the results of the soundpressure levels Vd. FIG. 29C shows a curve 116 of actual temperaturechanges in the snow removal base (see FIG. 25) in the same month(January, 2001).

As shown in FIG. 29B, as with the forecast for December, the weatherforecasting curve 114 of the long-term weather forecast indicates a coldclimate with lower temperatures than the monthly average temperature inthe past throughout January. It can thus be predicted that it will becold up to the end of January following December, based on the measureddata in October. The curve 116 of actual temperature changes shown inFIG. 29C indicates that the temperature below 0° C. continued from thestart to end of the month, in a pattern corresponding to the weatherforecasting curve 114 shown in FIG. 29B.

FIG. 30A shows a measured curve 118 based on changes in the soundpressure level Vd in Nagaoka City, Niigata Prefecture (FIG. 25), inAugust, 2000. FIG. 30B shows a weather forecasting curve 120 of along-term weather forecast in the vicinity of Nagaoka City in February,2001 (after six months), predicted from the results of the soundpressure levels Vd. FIG. 30C shows a curve 122 of actual temperaturechanges in the snow removal base (FIG. 25) in the same month (February,2001).

As shown in FIG. 30B, the weather forecasting curve 120 of the long-termweather forecast indicates a cold climate with lower temperatures thanthe monthly average temperature in the past at the start of February,but indicates a warmer climate toward the end of February. It can thusbe predicted that it will be cold at the start of February, but willbecome warmer at the end of February, based on the measured data inAugust. The curve 122 of actual temperature changes shown in FIG. 30Cindicates that the temperature below 0° C. continued at the start of themonth, but rose to about 0° C. at the end of the month, in a patterncorresponding to the weather forecasting curve 120 shown in FIG. 30B.

FIG. 31A shows a measured curve 124 based on changes in the soundpressure level Vd in Nagaoka City, Niigata Prefecture (FIG. 25), inSeptember, 2000. FIG. 31B shows a weather forecasting curve 126 of along-term weather forecast in the vicinity of Nagaoka City in March,2001 (after six months), predicted from the results of the soundpressure levels Vd. FIG. 31C shows a curve 128 of actual temperaturechanges in the snow removal base (FIG. 25) in the same month (March,2001).

As shown in FIG. 31B, the weather forecasting curve 126 of the long-termweather forecast stays nearly centrally in the graph throughout March.The weather forecasting curve 126 predicts, therefore, that, unlike theforecasts for January and February, in March it will be warm withrelatively high temperatures close to the average monthly temperature inthe past in the entire month. The curve 128 of actual temperaturechanges shown in FIG. 31C indicates that the temperature near 0° C.continued from the start of the month to a middle part of the month, butrose above 0° C. at the end of the month, in a pattern corresponding tothe weather forecasting curve 126 shown in FIG. 31B.

The measured curves of the sound pressure levels Vd and the long-termweather forecasting curves shown in FIGS. 27A through 31C are displayedon the screen of the display unit 54 shown in FIG. 1, and also outputtedas a hard copy from the printing unit 58 for use by the user.

According to the third embodiment described above, based on the findingby the inventor that a climate three months ahead of a measured monthchanges in phase with the climate in the measured month and a climatesix months ahead of the measured month changes in opposite phase withthe climate in the measured month, a long-term weather forecast can bemade to predict climate conditions such as cold and warm temperaturesafter three or six months much more accurately than with theconventional forecasting apparatus, based on measured data of sounds Pfrom the earth in the measured month. It is also expected that a climatenine months after the measured month changes in phase with the climatein the measured month and a climate twelve months after the measuredmonth changes in opposite phase with the climate in the measured month.

The periods of three months and six months referred to above aredetermined based on the length of one year. Specifically, if the lengthof one year is 365 days and 6 hours, then the length of three months is(365×24+6)× 3/12=2191.5 hours, i.e., 91 days, 7 hours, and 30 minutes,and the length of six months is 182 days and 15 hours.

As shown in FIG. 32, a country, such as Japan 200, is divided intosquare areas each having sides, 20 km long, and a telemeter includingthe vibration sensor 12, the sound observing device 14, and the dataprocessing device 16 and having a data transmitting function is placedin or near each point of intersection of the sides of square areas. Thetelemeters serve as observation points for observing sounds from theearth. Data representing observed sounds from the earth are transmittedat fixed times to a certain location, not shown, where a data analyzingapparatus and a forecasting apparatus are located. In response to thedata transmitted from the telemeters, the data analyzing apparatus andthe forecasting apparatus draws a present plot of isobars 204 ofobserved sounds from the earth as shown in FIG. 33. Based on an isobaricrepresentation of the isobars 204, a plot of isobars after three or fixmonths can be drawn to predict long-term weather conditions not only atthe observation points but also over the entire country.

According to the present invention, it is possible to forecast long-termweather conditions such as warm and cold climates related to high andlow temperatures highly accurately based on the present magnitude ofsounds from the earth.

According to the present invention, furthermore, it is possible toaccurately watch and forecast slope failures such as landslides, etc.,and it is possible to watch and forecast slope failures such aslandslides, etc. according to a simple process. Therefore, the costrequired to watch and forecast slope failures such as landslides, etc.may be relatively low.

Although certain preferred embodiments of the present invention havebeen shown and described in detail, it should be understood that variouschanges and modifications may be made therein without departing from thescope of the appended claims.

1. An apparatus for forecasting a slope failure, comprising: means formeasuring sounds from the earth; and forecasting means for forecasting aslope failure based on a change in the measured sounds from the earth.2. An apparatus according to claim 1, wherein said means for measuringsounds from the earth comprises: means for measuring said sounds fromthe earth through a tree on the earth.
 3. An apparatus according toclaim 1, wherein said forecasting means comprises: means for forecastinga slope failure when said means for measuring sounds from the earthmeasures a sound from the earth having a frequency ranging from 30 to200 Hz.
 4. An apparatus according to claim 3, wherein said forecastingmeans comprises: means for presuming a sound produced by a rupture of aroot of said tree when said means for measuring sounds from the earthmeasures a sound from the earth having a frequency ranging from 100 to160 Hz, and presuming a sound produced by a land movement when saidmeans for measuring sounds from the earth measures a sound from theearth having a frequency ranging from 30 to 50 Hz.
 5. An apparatusaccording to claim 3, wherein said forecasting means comprises: meansfor presuming a sound produced by an underground water flow when saidmeans for measuring sounds from the earth measures a sound from theearth continuously.
 6. An apparatus according to claim 1, furthercomprising: means for, when said means for measuring sounds from theearth measures said sounds from the earth simultaneously in at leastfour sites, calculating a position in which said sounds from the earthare produced, based on a simultaneous observation of said sounds fromthe earth in said at least four sites.
 7. An apparatus according toclaim 2, further comprising: means for, when said means for measuringsounds from the earth measures said sounds from the earth simultaneouslyin at least four sites, calculating a position in which said sounds fromthe earth are produced, based on a simultaneous observation of saidsounds from the earth in said at least four sites.
 8. A system forforecasting a slope failure, comprising: means for measuring sounds fromthe earth; means for capturing a ground surface image; and means forforecasting a slope failure based on a change in the measured soundsfrom the earth and a change in the captured ground surface image.
 9. Asystem according to claim 8, wherein said means for measuring soundsfrom the earth comprises means for measuring sounds from the earththrough a tree on the earth, and said means for forecasting a slopefailure comprises means for capturing images chronologically anddetecting a change in the ground surface image based on a differencebetween the chronologically captured images.
 10. A system according toclaim 8, wherein said means for forecasting a slope failure forecasts aslope failure when said means for measuring sounds from the earthmeasures a sound from the earth having a frequency ranging from 30 to200 Hz and said means for capturing a ground surface image detects achange in the captured ground surface image.
 11. A system according toclaim 8, further comprising: means for, when said means for measuringsounds from the earth measures said sounds from the earth simultaneouslyin at least four sites, calculating a position in which said sounds fromthe earth are produced, based on a simultaneous observation of saidsounds from the earth in said at least four sites.
 12. A method offorecasting a slope failure, comprising the steps of: measuring soundsfrom the earth; and forecasting a slope failure based on a change in themeasured sounds from the earth.
 13. A method according to claim 12,further comprising the steps of: capturing a ground surface image; andforecasting a slope failure based on a change in the measured soundsfrom the earth and a change in the captured ground surface image.